Modern day organizational environments are heavily dependent on computing and communication systems for execution of their tasks. An organization's workforce may be primarily interacting with its computing systems in carrying out its various duties. The increasing use of computing systems to execute various complex tasks has given rise to Artificial Intelligence (AI) technologies wherein smart machines capable of independent decision making are developed. Various reasons such as development of computational resources capable of processing large amount of data, the explosive growth of data that is available for processing (Big Data), the focus on specific tasks or problems and development of machines capable of receiving feedback and improving thereon are a few of the reasons for the rise of AI technologies in our everyday life.
The research associated with AI is highly technical and specialized. Some of the tasks involved in developing machines with AI can include programming computers to acquire traits such as knowledge, reasoning, problem solving, perception, planning and ability to manipulate and move objects. Machine learning (ML) and natural language processing (NLP) are important parts of AI. ML involves mathematical analysis of various ML algorithms and their performances. Teaching machines human skills such as reasoning, problem solving and decision making can be a difficult and tedious task requiring a highly trained workforce.